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FOND planning for pure-past linear temporal logic goals

Abstract:
Recently, Pure-Past Temporal Logic (PPLTL) has proven highly effective in specifying temporally extended goals in deterministic planning domains. In this paper, we show its effectiveness also for fully observable nondeterministic (FOND) planning, both for strong and strong-cyclic plans. We present a notably simple encoding of FOND planning for PPLTL goals into standard FOND planning for final-state goals. The encoding only introduces few fluents (at most linear in the PPLTL goal) without adding any spurious action and allows planners to lazily build the relevant part of the deterministic automaton for the goal formula on-the-fly during the search. We formally prove its correctness, implement it in a tool called Plan4Past, and experimentally show its practical effectiveness.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.3233/faia230281

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author


Publisher:
IOS Press
Host title:
ECAI 2023
Pages:
279-286
Series:
Frontiers in Artificial Intelligence and Applications
Series number:
372
Publication date:
2023-09-28
Acceptance date:
2023-07-15
Event title:
26th European Conference on Artificial Intelligence (ECAI 2023)
Event location:
Kraków, Poland
Event website:
https://ecai2023.eu/
Event start date:
2023-09-30
Event end date:
2023-10-04
DOI:
EISSN:
1879-8314
ISSN:
0922-6389
EISBN:
9781643684376
ISBN:
9781643684369


Language:
English
Pubs id:
1765193
Local pid:
pubs:1765193
Deposit date:
2024-04-14
ARK identifier:

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